1. Field of the Invention
The present invention relates to biometric information verifying apparatus which verify users by use of biometrics information such as fingerprints, palm prints, blood vessel patterns, iris patterns, facial images. The apparatus verifies biometric information images input by users at the time of verification against biometric information images registered in advance at enrollment. The invention particularly relates to biometric information verifying apparatus in which a pattern matching method of image verification is employed.
2. Description of the Related Art
Pattern matching is a method commonly used in extracting human figure images, facial images, or specific object images such as vehicles, from picture images. The method is also widely used in user verification utilizing biometric information such as fingerprints, palm prints, blood vessel patterns, iris patterns, and facial images. The application of this pattern matching is not limited to verification between two-dimensional images, and it also covers one-dimensional signal recognition such as voice recognition.
Here, concrete examples of pattern matching employed in fingerprint image verification will be described hereinbelow, referring to relevant drawings. FIG. 21A and FIG. 21B show fingerprint images 1 and 2 to be subjected to pattern matching. Referring to FIG. 22A through FIG. 22C, a description will now be given of procedures of pattern matching between the fingerprint image 1 of FIG. 21A and the fingerprint image 2 of FIG. 21B. Note that the fingerprint image 1 is simply outlined in these drawings so that overlap between the two fingerprints, 1 and 2, can be clearly seen.
The basics of pattern matching lie in searching a position where the degree of overlap between two object images, 1 and 2, is a maximum (or where the two images are overlapped best), while shifting the two object images, 1 and 2, little by little, to evaluate the overlap degree.
For instance, the image 1 of FIG. 21A is laid over the image 2 of FIG. 21B, and the image 1 is then gradually shifted in the x direction or the y direction, as shown in FIG. 22A and FIG. 22B, to find a position of FIG. 22C where the overlap degree between the two images 1 and 2 is a highest value. The overlap degree is evaluated at that position, whereby the two images 1 and 2 are verified against each other (whether or not the two images 1 and 2 are matched with each other, that is, whether or not the two fingerprint images belong to the same person).
The degree of overlap between the images 1 and 2 is obtained by the following computation. The product of the pixel values of an individual pair of overlapping pixels, one from the image 1 and the other from the image 2, is calculated, and such products obtained from the individual overlapping pixel pairs are summed up in an overlap area between the two images 1 and 2, thereby obtaining the degree of overlap therebetween. The better the images 1 and 2 match with each other, the larger the thus calculated overlap degree becomes. Therefore, when fingerprint or facial images are subjected to verification, a match decision between the object images is often made depending on the overlap degree. That is, if the overlap degree exceeds a predetermined threshold, it is judged that the images match up with each other.
Such a simple algorithm of pattern matching facilitates its implement. However, since the calculation of the overlap degree between the images 1 and 2 needs to use all the pixel values of the two object images 1 and 2, not only the verification operation amount is increased but also the registered data amount is extremely increased.
Hence, as shown in FIG. 23, there has been developed a technique in which both the fingerprint images {one is a previously registered fingerprint image; the other is a fingerprint image (to-be-verified fingerprint image) input by a user at verification}, which is to be subjected to pattern matching, are divided into cells, and pattern matching processing is carried out on the thus divided images.
This technique extracts a data set (ridge direction θ, pitch λ, and offset amount δ) such as that which is disclosed in the following non-patent document 1, as cell basic information, from the individual cells (see FIG. 24B). Here, as shown in FIG. 24B, ridge direction θ is the direction of the normal to a ridge contained in each cell; ridge pitch λ is the amount of spacing between adjacent ridges contained in the cell; offset amount δ is a minimum distance from the reference point (for example, the lower-left corner of a cell) to the closest ridge in the cell.
FIG. 23 is an example fingerprint image which is divided into cells; FIG. 24A is a view showing an example cell, which is one of the cells that are obtained by dividing a fingerprint image into cells; FIG. 24B is a view for use in describing cell basic information extracted and obtained from the cell of FIG. 24A.
When a fingerprint image is stored as a registered fingerprint image, the three parameters θ, λ, and δ of the individual cells are stored instead of the image information itself, whereby the registered data amount is greatly reduced.
Further, at verification between the two fingerprint images, cell basic information (to-be-verified data) extracted from the individual cells of the to-be-verified fingerprint image is compared with registered cell basic information (registered data) that was previously extracted from the registered fingerprint image. If the comparison result satisfies a predetermined condition, it is judged that the two images match up with each other. With this arrangement, the verification operation amount is greatly reduced in comparison with the pattern matching that uses image information itself.
[Non-patent document 1] ISO/IEC JTC 1/SC 37 N313 (2003-10-3; 2nd Working Draft Text for 19794-3, Biometric Data Interchange Formats-Part 3: Finger Pattern Data), [searched on Feb. 6, 2004], on the Internet <URL: http://www.jtcl.org/navigation.asp?Mode=Browse&Area=Document&SubComm=ISO/IECJTClSC00037&CommLevel=SC&SCCOD E=SC+37>
According to the above previous art, cell basic information extracted from the individual cells is stored and is then used in verification in place of image information itself, thereby greatly reducing the registered data amount and the verification operation amount. However, the art is disadvantageous in that it can use only fingerprint shape information in pattern matching (verification), totally ignoring information of fingerprint minutiae (ridge bifurcations and endings).
In this manner, the previous art has a problem that it is difficult to utilize minutia information, which is the most defining feature in fingerprints, in pattern matching (verification), so that the false verification rate is difficult to be lowered.